Bringing employee learning to AI stress research: A moderated mediation model

IF 12.9 1区 管理学 Q1 BUSINESS
Qiwei Zhou , Keyu Chen , Shuang Cheng
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引用次数: 0

Abstract

While a substantial portion of the literature characterizes artificial intelligence (AI) stress as a hindrance, our focus diverges by probing employee learning as an active response to this challenge. We highlight the role of employee knowledge and skills development amidst an enterprise's digital transformation. Drawing on the active learning perspective of the Job Demand-Control model, we investigate why and when AI stress promotes employee learning and subsequent adaptive coping behaviors. We propose that AI stress can create opportunities and resources for employee learning, leading to improved job performance and supportive behavior for digital transformation. Additionally, we examine how employee trust in AI moderates these relationships, finding that higher levels of AI trust are associated with greater use of active learning strategies when faced with AI stress. Our findings, based on a two-wave survey of 224 employees from a motor-vehicle testing company in China, are further supported by post-hoc interview data collected from 32 employees of the same company. Overall, our study contributes to the understanding of AI adoption, digital transformation, and stress learning.
将员工学习引入人工智能压力研究:调节中介模型
大量文献将人工智能(AI)压力描述为一种阻碍,而我们的研究重点则有所不同,我们将员工学习作为应对这一挑战的一种积极措施。我们强调员工知识和技能发展在企业数字化转型中的作用。借鉴 "工作需求-控制 "模型的主动学习视角,我们研究了人工智能压力促进员工学习和后续适应性应对行为的原因和时间。我们提出,人工智能压力可以为员工学习创造机会和资源,从而提高工作绩效并支持数字化转型行为。此外,我们还研究了员工对人工智能的信任如何调节这些关系,发现人工智能信任度越高,员工在面对人工智能压力时使用主动学习策略的比例就越高。我们的研究结果基于对中国一家机动车检测公司 224 名员工进行的两波调查,并得到了同一公司 32 名员工的事后访谈数据的进一步支持。总之,我们的研究有助于理解人工智能的应用、数字化转型和压力学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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